Header

UZH-Logo

Maintenance Infos

Reliable detection of subclonal single-nucleotide variants in tumour cell populations


Gerstung, Moritz; Beisel, Christian; Rechsteiner, Markus; Wild, Peter; Schraml, Peter; Moch, Holger; Beerenwinkel, Niko (2012). Reliable detection of subclonal single-nucleotide variants in tumour cell populations. Nature Communications, 3:811.

Abstract

According to the clonal evolution model, tumour growth is driven by competing subclones in somatically evolving cancer cell populations, which gives rise to genetically heterogeneous tumours. Here we present a comparative targeted deep-sequencing approach combined with a customised statistical algorithm, called deepSNV, for detecting and quantifying subclonal single-nucleotide variants in mixed populations. We show in a rigorous experimental assessment that our approach is capable of detecting variants with frequencies as low as 1/10,000 alleles. In selected genomic loci of the TP53 and VHL genes isolated from matched tumour and normal samples of four renal cell carcinoma patients, we detect 24 variants at allele frequencies ranging from 0.0002 to 0.34. Moreover, we demonstrate how the allele frequencies of known single-nucleotide polymorphisms can be exploited to detect loss of heterozygosity. Our findings demonstrate that genomic diversity is common in renal cell carcinomas and provide quantitative evidence for the clonal evolution model.

Abstract

According to the clonal evolution model, tumour growth is driven by competing subclones in somatically evolving cancer cell populations, which gives rise to genetically heterogeneous tumours. Here we present a comparative targeted deep-sequencing approach combined with a customised statistical algorithm, called deepSNV, for detecting and quantifying subclonal single-nucleotide variants in mixed populations. We show in a rigorous experimental assessment that our approach is capable of detecting variants with frequencies as low as 1/10,000 alleles. In selected genomic loci of the TP53 and VHL genes isolated from matched tumour and normal samples of four renal cell carcinoma patients, we detect 24 variants at allele frequencies ranging from 0.0002 to 0.34. Moreover, we demonstrate how the allele frequencies of known single-nucleotide polymorphisms can be exploited to detect loss of heterozygosity. Our findings demonstrate that genomic diversity is common in renal cell carcinomas and provide quantitative evidence for the clonal evolution model.

Statistics

Citations

75 citations in Web of Science®
78 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

1 download since deposited on 01 Oct 2012
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2012
Deposited On:01 Oct 2012 12:25
Last Modified:07 Dec 2017 15:12
Publisher:Nature Publishing Group
ISSN:2041-1723
Publisher DOI:https://doi.org/10.1038/ncomms1814
PubMed ID:22549840

Download